Quantpedia contacted me a few months ago and asked if I’d be interested in reviewing their site on my blog. I’m always looking for new ideas for trading systems, so I said “sure!” (Disclosure: they provided me with free account access during the review period.) Quantpedia.com is an

I looked at the chart for SPY just now, and thought, “Huh…two days in a row that have gapped up. Wonder if that’s significant in any way?” By “gap,” I mean that today’s low was higher than yesterday’s high. When this happens two days in a row, does it mean we should use quintuple

Back in June of 2016, I wrote this post about random entries and trailing exits. It turns out (on average) that you can beat buy-and-hold of the S&P 500 by simply buying members of the S&P 100 randomly, as long as you a) have a market-timing filter, and 2) have a trailing stop of 20%. Yes

This is kind of a weird one. I was mulling over the question of what happens when the market opens up, i.e. above its previous close. Is the day likely to be an up day? A down day? I got out my data and started poking around. I looked at all “open-up” days with an open at least 0.25% above the

In the last post (here), I examined what happened after a stock moved down a significant multiple of its previous day’s Average True Range (ATR20 in this case). Stocks tended to have up days on day 1 and days 3-5, with a down day on day 2 as an average. What about bursts upward? Are they the

When stocks are moving gently from one day to the next, there is often no discernible pattern. However when they start rockin' and rollin' one direction or the other, they show certain similarities. I'm always curious how stocks behave when they show a significant drop, or when they

Above: long-exposure nighttime shot of oil rigs off the coast of California. Strange things happen to options and futures on fairly predictable dates. Options expiration dates, contract settlement dates…these are trading days where – and this is just my theory – some traders just want to get

Yesterday I discussed two swing-trade systems that work pretty well in out-of-sample data. While each works differently, they overlap enough that you don’t get any benefit from running them both at the same time. One great thing about these two systems is that they’re dead simple to manage.

Ah…leveraged ETFs. All that beta without all the embarrassment of trying to borrow money from your broker (or cousin) to leverage your returns. Is the regular ETF not volatile enough for you? Buy the 2x version! Still too tepid? Perhaps the 3x version is what you’re looking for. Unless you’re

In the last post, I compared three systems that traded the same instrument (SPY) in different ways, and also compared the combination of the three systems. Combining those systems reduced risk, which allowed us to increase our position size (either through more cash or using leverage). We could then

Which color do you like better? Green or brown? I’m partial to the green curve myself. That green curve comes from writing puts…sort of. Writing puts can be a lower volatility play that makes you money in choppy or flat markets, falls more softly in down markets, and seriously under-performs

Happy new year! It’s that time again, when everyone with a blog does a wrap up of the previous year. Here’s my look-back. Many of you follow along with the “+/-30% per quarter wider-market breadth indicator”. Which is too much of a mouthful, so I’ve humbly named it after myself instead. I

Happy New Year, one day early. Here’s wishing 2017 is successful for you in whichever way you define success. Aren’t calendars wonderful? A couple of days ago, up pops a reminder on my calendar to revisit a post I did a year ago. At the very beginning of 2016, I wrote a post on whether yearly

When I start to write a blog post, usually my process is this: Come up with a really bad pun for the title. Write the rest of it. Bad puns are an important part of finance, and life in general. A blog reader contacted me recently to chat about various technical analysis indicators, and one he

As traders, we spend a lot of time thinking about our entries into a trade. What stock, commodity or currency to choose, when is the best timing, etc. But what if the entries don’t matter? What if trading is all about the exits? Ok, that’s a really simple-minded statement, but I’m a little

Here’s a free system for you. I call it the “SPY RSI No Lie” system. It’s called that because I like stupid titles, and internal rhymes are an added plus. I read a post on Jeff Swanson’s System Trader Success recently about using a short-period RSI value to trigger trades with the S&P

A reader of my blog, Matt B., commented recently on an old post I’d written about momentum bursts. Like me, Matt was intrigued by the short 3 to 5-day momentum bursts he saw described time and again on Pradeep Bonde’s stockbee site. Those bursts look so pretty, so elegant, and more to the point:

A common tactic for some traders is to scale out of successful positions. The logic is this: I’ve already made some money, so I want to hold onto some of that. I’ll cash out a portion of my trade now, and see how the trade continues, but with reduced risk. You see this behavior with day traders,

In a recent blog post, I rather glibly stated that the market tends to revert to a mean. A reader called me out about the time frame I was using, which raises a good point. A market can tend toward both mean reversion and momentum over different time frames. Many traders would argue that different

I have got a great trading system for you. I mean, look at that equity curve! It’s very straight, no drawdowns, and $30,000, compounded, became almost $120,000 over time. What’s the catch? They say (and I’m not sure who “they” are) that the average retail investor hates to book a loss, and

Here’s a stupid system. In fact, I call it the “Stupid 10 Days” system. You look at the last ten days of trading. If the market at the closing bell is up from the market close of 10 days ago, you buy at the next open. You hold for 10 days, then sell at the next open. A classic momentum play.

This all started over the weekend, when I started wondering about a trade I had going. The trade hadn’t hit my profit target on Friday and so carried over through the weekend. I started wondering about day-of-week ‘seasonality’ and thought I’d bust out the old charts and see what’s up.

That graph looks like a bunch of spaghetti, I realize. But I’ll explain! I’m back testing Genotick. It’s an open-source machine-learning java script. Probably to the developer’s dismay, I’m always throwing things at it to make it break. Much like a small child throwing a temper tantrum,

I read a blog post recently that began “suppose you have a trading system that works well on low-volatility days…” and I thought, hmm. Is that a thing? Is there an edge to low-volatility days vs high volatility days? Let’s turn this blog post into a speculator’s version of Dude, What Would

I’m running a high risk of running out of movies with “short” in the title. So this had better be the last blog post on the subject! In my previous post (here), I looked at a short-sale signal where a stock was shorted after it averaged 3% gains each day over five days (in any distribution).

So in this last post, I data-mined the hell out of the S&P500 index (well ok SPY) and found an “anomaly”: every time SPY drops more than 1% from the previous close to the current close, you wait (that’s Day 0). You then buy at the close 13 days later, and sell at the close of Day 14. This

I’ve been reading books by Michael Halls-Moore and my head hurts. Not having any formal training in statistics, I only understand about half of the material. None the less, I found his discussion of ‘correlograms’ interesting. I even installed R on my computer (even though I haven’t fully

I seem to be in a ‘shorting’ mood lately. Can’t think why that might be… (oh yeah, the general state of the market perhaps?). Above and below you can see some recent examples of stocks that went up a lot, and then either kept going up or dropped down again. Yes, that amazing analysis is

I’ve been teaching myself Python, and I’ve had a couple of successes recently where I took a concept or “need” and coded it to completion. Yay, me! One thing I find myself doing a lot is sorting a batch of data by one column in Excel/Google Sheets, then dividing up another column into

In hindsight, it’s fun to look at stocks that have had a huge surge, only to collapse violently after they peak. And by “fun” I mean sitting on the sidelines watching, as opposed to pulling one’s hair out when you’re long that particular trade. Above you can see Apple (AAPL) in 2008, where

Recently I posted a number of articles on various breadth diffusion indicators and their relative effectiveness in predicting the health of the S&P 500. The big winner was the system that compared the number of stocks in the historical constituents of the Russell 3000 that were up 30% or more

A reader on my blog (Thanks Kris!) suggested that I explore how much noise is needed to send Genotick off the deep end. You’ll recall from my earlier post on the subject that I was looking for hidden biases that Genotick might have, and explored how it responded to pure and noisy sine waves of

Today marks the sixth day in the row that the S&P 500’s RSI(2) value was under 25.* Since Jan 1 2000, this has happened only 15 times prior to today. So I thought it would be fun to see what the forward return has been after these events. Here’s a handy spreadsheet. I calculated the forward

I have been playing around with Genotick some more, the open-source genetic learning trading software by Lukasz Wojtow. One thing that has been puzzling me is that the software seems to do well on certain types of data, but not others. And I’m having trouble identifying what sort of data it’s

Apparently it’s easy to beat the market. Randomly-selected stocks can beat the market, as recently discussed on the Predictive Alpha website. You can even beat the market just by choosing stocks whose names begin with the letters that make up your own name (as discussed in an amusing blog post by

I’ve recently been experimenting with Genotick, which is open-source java software that attempts to discover mechanical trading systems through the use of machine learning. You can run it on just about any Mac/Windows/Linux system (although you may have additional hurdles to get java8 working at

As per request, I’m including the AmiBroker code for the “30% up/down last quarter in the Russell 3000 index” indicator. I REALLY need to come up with a better name for it than that. How about the Haines Breadth Indicator? No, that’s stupid. Magic Matt’s Mystical Meter? Uh…sure. It’s a

Let’s wrap this up! We established a baseline using a moving-average system on the price of SPY to determine when we enter and exit the market. Then we tested a variety of breadth indicators, using the diffusion calculation and requiring entries and exits to have ten days above or below the

This is part 5 of a multi-part series examining the use of market breadth indicators to judge the state of the market. For an overview of what I’m doing, you’d best start here so you can catch up: PART 1…CLICK HERE. And oh yeah, we finally have an indicator that beats our baseline! Just

Welcome to Part 4 of this series. We’re still trying to find a market breadth indicator that gives a better health assessment than using a simple moving average on SPY. For a description of what the heck I’m doing, please go back and read the first post (and the subsequent ones too): Using

If you’re just popping in during the middle of this series, I suggest that you go read the intro post first, so you know what the heck I’m talking about. I’ll wait here while you check it out: Using Market Breadth to Gauge Market Health (part 1) Let’s next take a look at a short-term breadth

Welcome to part two of an ongoing series, where I look at different breadth indicators and their viability in describing market health. You can read – and should read! – the introductory post here: Using Market Breadth to Gauge Market Health (part 1) So last post, we (ok, “I”, since I’m

We all want to know if it's the right time to trade. And we'd also like to know which direction. So for at least the last two months like forever, investors have tried to come up with ways to judge how the market is doing. One technique is to use market breadth as an indicator. There are a